Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-

Overcoming limitations of modelling rare species by using ensembles of small models

1. Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. 2. For each species numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These 'ensembles of small models' (ESMs) were compared to standard Species Distribution Models (SDMs) using three commonly used modelling techniques (GLM, GBM, Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. 3. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were independently evaluated using a transferability assessment. 4. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Todennäköisyyspohjaisen kaapelipaloriskianalyysimenetelmän kehittäminen ydinvoimalaitokselle

Ydinenergian tuottamisessa turvallisuus on tärkeää. Todennäköisyyspohjaisella riskianalyysillä voidaan arvioida turvallisuusvaatimusten täyttymistä eri tilanteissa. Tässä diplomityössä tarkastellaan todennäköisyyspohjaisen riskianalyysin käyttöä ydinvoimalaitoksen kaapelipalojen vaikutusten arvioinnissa. Työn tarkoituksena on omalta osaltaan edistää ydinvoimalaitosten kaapelipaloturvallisuuden parantamista. Työssä esitellään todennäköisyyspohjaisen riskianalyysin ja todennäköisyyspohjaisen paloanalyysin periaatteet sekä nykyiset kaapelipaloanalyysimenetelmät. Olemassa olevien menetelmien pohjalta kehitettiin menetelmä Olkiluoto 1 ja 2 laitosyksiköiden kaapelipaloturvallisuuden arviointiin. Työssä tarkastellaan myös maailmalla sattuneita kaapelipaloja sekä ydinvoimalaitosten palosimulointiin kehitettyä ohjelmistoa. Työssä kehitetty kaapelipaloanalyysi jakautuu kahteen päävaiheeseen: virtapiirien vika-analyysiin ja virtapiirivikojen todennäköisyysanalyysiin. Virtapiirien vika-analyysi käsittää kaapeleiden vikamoodien, virtapiirien vikaantumisluokkien sekä vikaantumisten vaikutuksien määrittämisen. Virtapiirivikojen todennäköisyysanalyysissä määritetään puolestaan vikaantumistodennäköisyydet kaapelipalokokeiden tulosten pohjalta. Kehitettyä analyysimenetelmää sovellettiin esimerkinomaisesti Olkiluoto 1 ja 2 laitosyksiköiden kahdelle eri huonetilalle. Tuloksena saatiin turvallisuudelle tärkeiden järjestelmien virtapiirien vikaantumismallit sekä niiden todennäköisyydet. Tulosten perusteella voidaan todeta, että työssä kehitetty kaapelipaloanalyysimenetelmä toimi hyvin. Tulevaisuudessa menetelmää on tarkoitus hyödyntää Olkiluoto 1 ja 2 -laitosyksiköiden kaapelipaloturvallisuuden arvioinnissa.

Combining niche modelling and landscape genetics to study local adaptation: A novel approach illustrated using alpine plants

Understanding the factors that shape adaptive genetic variation across species niches has become of paramount importance in evolutionary ecology, especially to understand how adaptation to changing climate affects the geographic range of species. The distribution of adaptive alleles in the ecological niche is determined by the emergence of novel mutations, their fitness consequences and gene flow that connects populations across species niches. Striking demographical differences and source sink dynamics of populations between the centre and the margin of the niche can play a major role in the emergence and spread of adaptive alleles. Although some theoretical predictions have long been proposed, the origin and distribution of adaptive alleles within species niches remain untested. In this paper, we propose and discuss a novel empirical approach that combines landscape genetics with species niche modelling, to test whether alleles that confer local adaptation are more likely to occur in either marginal or central populations of species niches. We illustrate this new approach by using a published data set of 21 alpine plant species genotyped with a total of 2483 amplified fragment length polymorphisms (AFLP), distributed over more than 1733 sampling sites across the Alps. Based on the assumption that alleles that were statistically associated with environmental variables were adaptive, we found that adaptive alleles in the margin of a species niche were also present in the niche centre, which suggests that adaptation originates in the niche centre. These findings corroborate models of species range evolution, in which the centre of the niche contributes to the emergence of novel adaptive alleles, which diffuse towards niche margins and facilitate niche and range expansion through subsequent local adaptation. Although these results need to be confirmed via fitness measurements in natural populations and functionally characterised genetic sequences, this study provides a first step towards understanding how adaptive genetic variation emerges and shapes species niches and geographic ranges along environmental gradients.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Study and modelling of the effect of herbicides pulse exposure on freshwater microalgae

De plus en plus de substances chimiques sont émises et détectées dans l'environnement.Parmi ces substances, on trouve les herbicides qui sont utilisés en agriculture pour luttercontre la présence des mauvaises herbes. Après leur application sur les sols, les herbicidespeuvent être entrainés par les eaux de pluie jusque dans les ruisseaux et les rivières. Lesconcentrations de ces substances varient donc de manière importante dans les systèmesaquatiques en période de pluie ou en période de temps sec. Des pics élevés de concentrationssont suivis de période de concentrations très faibles ou nulles. Les herbicides présents dans lescours d'eau peuvent engendrer des effets toxiques sur les algues et les plantes aquatiques. Orles tests classiques d'écotoxicologie effectués en laboratoire sont réalisés en exposant lesespèces vivantes à des polluants de manière continue. Ils ne permettent donc pas d'évaluer leseffets des concentrations fluctuantes comme celles des herbicides. Le but de cette thèse estd'étudier et de modéliser les effets des concentrations fluctuantes d'herbicide sur les espècesde microalgues vertes Scenedesmus vacuolatus et Pseudokirchneriella subcapitata. Desexpériences en laboratoire ont également été effectuées dans le but de valider le modèle.Quatre herbicides ont été testés. Il s'agit de l'atrazine (utilisé jusqu'à récemment pour lemaïs), du diuron (utilisé dans la vigne), de l'isoproturon (utilisé pour les céréales) et du Smétolachlore(utilisé pour le maïs). Les résultats de ce travail de thèse indiquent que les effetsdes concentrations fluctuantes d'herbicide peuvent être modélisés sur des algues d'eau douce.Le modèle est relativement simple pour les inhibiteurs de la photosynthèse tels que l'atrazine,le diuron ou l'isoproturon. Il nécessite la connaissance de deux paramètres, le taux decroissance de l'algue sans polluant et la courbe dose-réponse pour chaque substance.Cependant, des expériences supplémentaires doivent être réalisées si la substance étudiéeinduit un délai de l'effet et du rétablissement ou si une algue est cultivée avec une autre alguedans le même milieu de croissance. Le modèle pourrait également être adapté pour tenircompte des mélanges de substances. Appliqué pour prédire les effets sur les algues descénarios réels, le modèle montre que les longs pics de concentrations jouent le rôle le plusimportant. Il est donc crucial de les mesurer lors du monitoring des cours d'eau. D'autre part,une évaluation du risque effectuée avec ce modèle montre que l'impact des pics deconcentrations sur les espèces les plus sensibles est total. Cela met en évidence, une fois deplus, l'importance de tenir compte de ces concentrations fluctuantes dans l'évaluation durisque environnemental des herbicides, mais également des autres polluants.

Animal modelling for inherited central vision loss.

Disease-causing variants of a large number of genes trigger inherited retinal degeneration leading to photoreceptor loss. Because cones are essential for daylight and central vision such as reading, mobility, and face recognition, this review focuses on a variety of animal models for cone diseases. The pertinence of using these models to reveal genotype/phenotype correlations and to evaluate new therapeutic strategies is discussed. Interestingly, several large animal models recapitulate human diseases and can serve as a strong base from which to study the biology of disease and to assess the scale-up of new therapies. Examples of innovative approaches will be presented such as lentiviral-based transgenesis in pigs and adeno-associated virus (AAV)-gene transfer into the monkey eye to investigate the neural circuitry plasticity of the visual system. The models reported herein permit the exploration of common mechanisms that exist between different species and the identification and highlighting of pathways that may be specific to primates, including humans.

Modelling the consequences of a reduction in alcohol consumption among patients with alcohol dependence based on real-life observational data.

BACKGROUND: Most available pharmacotherapies for alcohol-dependent patients target abstinence; however, reduced alcohol consumption may be a more realistic goal. Using randomized clinical trial (RCT) data, a previous microsimulation model evaluated the clinical relevance of reduced consumption in terms of avoided alcohol-attributable events. Using real-life observational data, the current analysis aimed to adapt the model and confirm previous findings about the clinical relevance of reduced alcohol consumption. METHODS: Based on the prospective observational CONTROL study, evaluating daily alcohol consumption among alcohol-dependent patients, the model predicted the probability of drinking any alcohol during a given day. Predicted daily alcohol consumption was simulated in a hypothetical sample of 200,000 patients observed over a year. Individual total alcohol consumption (TAC) and number of heavy drinking days (HDD) were derived. Using published risk equations, probabilities of alcohol-attributable adverse health events (e.g., hospitalizations or death) corresponding to simulated consumptions were computed, and aggregated for categories of patients defined by HDDs and TAC (expressed per 100,000 patient-years). Sensitivity analyses tested model robustness. RESULTS: Shifting from >220 HDDs per year to 120-140 HDDs and shifting from 36,000-39,000 g TAC per year (120-130 g/day) to 15,000-18,000 g TAC per year (50-60 g/day) impacted substantially on the incidence of events (14,588 and 6148 events avoided per 100,000 patient-years, respectively). Results were robust to sensitivity analyses. CONCLUSIONS: This study corroborates the previous microsimulation modeling approach and, using real-life data, confirms RCT-based findings that reduced alcohol consumption is a relevant objective for consideration in alcohol dependence management to improve public health.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.

Probabilistic graphical models to deal with age estimation of living persons

Due to the rise of criminal, civil and administrative judicial situations involving people lacking valid identity documents, age estimation of living persons has become an important operational procedure for numerous forensic and medicolegal services worldwide. The chronological age of a given person is generally estimated from the observed degree of maturity of some selected physical attributes by means of statistical methods. However, their application in the forensic framework suffers from some conceptual and practical drawbacks, as recently claimed in the specialised literature. The aim of this paper is therefore to offer an alternative solution for overcoming these limits, by reiterating the utility of a probabilistic Bayesian approach for age estimation. This approach allows one to deal in a transparent way with the uncertainty surrounding the age estimation process and to produce all the relevant information in the form of posterior probability distribution about the chronological age of the person under investigation. Furthermore, this probability distribution can also be used for evaluating in a coherent way the possibility that the examined individual is younger or older than a given legal age threshold having a particular legal interest. The main novelty introduced by this work is the development of a probabilistic graphical model, i.e. a Bayesian network, for dealing with the problem at hand. The use of this kind of probabilistic tool can significantly facilitate the application of the proposed methodology: examples are presented based on data related to the ossification status of the medial clavicular epiphysis. The reliability and the advantages of this probabilistic tool are presented and discussed.